Updated 4/11/2018
Here's my experience of installing the NVIDIA CUDA kit 9.0 on a fresh install of Ubuntu Desktop 16.04.4 LTS.
import duckdb | |
import fabduckdb | |
import gspread | |
import pandas as pd | |
def read_gsheet(service_account_json_path: str, gsheets_url: str, worksheet_name: str) -> pd.DataFrame: | |
gc = gspread.service_account(filename=service_account_json_path, scopes=gspread.auth.READONLY_SCOPES) | |
gsheet = gc.open_by_url(gsheets_url) | |
data = gsheet.worksheet(worksheet_name).get_all_records() |
call plug#begin('~/.vim/plugged') | |
Plug 'vim-airline/vim-airline' | |
Plug 'vim-airline/vim-airline-themes' | |
Plug 'scrooloose/nerdtree' | |
call plug#end() | |
let g:airline_powerline_fonts = 1 | |
set rtp+=/usr/local/opt/fzf | |
let g:NERDTreeDirArrowExpandable = '▸' |
Updated 4/11/2018
Here's my experience of installing the NVIDIA CUDA kit 9.0 on a fresh install of Ubuntu Desktop 16.04.4 LTS.
See Amato, Nancy M (1994) for details of the difference between separation (sigma: σ) and closest visible vertex (CVV).
Refer to P
and Q
as the two polygons with n
and m
vertices, respectively.
For the purposes of this discussion, a key insight is that it is enough to find the closest edge to each vertex in order to compute the minimum separation between P
and Q
.
This means iterating over all vertices, and finding a nearest neighbour. Thus, a time complexity in O((m + n) * log(m * n))
should be expected.